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Application of clustering methods for analysing of TTCN-3 test data quality

: Vega, D.; Taranu, S.; Din, G.; Schieferdecker, I.


Mannaert, H. ; IEEE Computer Society; International Academy, Research, and Industry Association -IARIA-:
Third International Conference on Software Engineering Advances, ICSEA 2008. Proceedings : Includes ENTISY 2008: International Workshop on Enterprise Information Systems ; 26 - 31 Oct. 2008, Sliema, Malta
Piscataway/NJ: IEEE, 2008
ISBN: 978-1-4244-3218-9
ISBN: 978-0-7695-3372-8
International Conference on Software Engineering Advances (ICSEA) <3, 2008, Sliema>
International Workshop on Enterprise Information Systems (ENTISY) <2008, Sliema>
Conference Paper
Fraunhofer FOKUS ()

The use of the standardised testing notation, Testing and Test Control Notation (TTCN-3) [5] language has increased continuously over the last years. Many test suites of large sizes covering different domains exist. Therefore, it becomes important to provide the TTCN-3 community with methods and tools to evaluate the quality of tests. This paper presents the idea of evaluating the quality of the test data stimuli by using a data clustering method and measuring the coverage related to data clusters. A cluster contains stimuli which are considered similar for the system under test (SUT) behaviour; that means that each stimuli within a cluster should provide similar results from the test point of view.